EAGER: Collaborative Mathematics Learning with Robots

这个PI团队询问(I)如何利用模块化机器人技术在学生小组中的个人之间分配工作，以促进那些学习代数的人更好地参与和更好地学习，以及(Ii)当学习者拥有支持分布式小组工作的技术时，从这种努力中可以学到什么更普遍的关于协调和支持学习的知识。机械工程师One Pi将一个新颖的模块化机器人平台带到了这次合作中，这个平台有很多支持代数学习的负担，非常吸引人，已经发现吸引了本来可能不会对数学学习感兴趣的学生，并且有支持分布式认知的负担，因此提出了一些促进和支持协作学习的新方法。第二位PI是一位学习科学家和数学教育研究员，他带来了数学学习方面的专业知识，并对如何利用分布式认知来促进协作数学学习有了细致入微的理解。协作学习的某些方面可能是第一次PI的机器人材料和围绕它们可以建立的项目解决挑战的独特方面所提供的。而且，使用这种操控可能会产生新的合作行为，这表明了促进学习的新途径。这个热切的项目支持在这两种方法之间创造协同效应的第一步，并将这些关于促进合作和数学学习的有趣想法具体化。这个项目的技术创新是学习如何使用具有支持分布式认知的负担能力的操纵器来促进协作，以及如何有效地将这种操纵器的使用与为协作解决数学问题而设计的软件相结合。这项研究旨在揭示如何利用能够支持分布式认知和协作学习的机械手，并发现一些新类型的协作行为，以及如何利用这些机械手来促进学习。教育目标既是更广泛的参与目标，也是学习目标，其想法是，在学习代数和其他学科的背景下，与参与机器人互动将吸引学生进入该学科领域，同时更好地促进他们的学习。尤其是代数，是通向更高级STEM的门户，要让更多的人进入STEM职业生涯，就需要吸引更多的人从事代数学习，并帮助更多的人学好代数。在性别和多样性方面，潜在的更广泛的影响尤其强烈。该项目代表了一个未经检验但可能具有变革性的想法的早期工作，并可能促进在使用模块化机器人和其他计算操作方面取得快速和创新的进展，以扩大对STEM学科的参与，并促进在这些学科中进行更深入的学习。

This PI team asks (i) how to use the affordances of modular robotics for distributing work among individuals in a student groups to promote both better engagement and better learning among those learning algebra and (ii) what can be learned more generally from this effort about orchestrating and supporting learning when learners have available to them technology that supports distributed group work. One PI, a mechanical engineer, brings a novel modular robotics platform to this collaboration, one that has many affordances for supporting algebra learning, is quite engaging and has been found to draw in students who otherwise might not become excited about math learning, and that has affordances for supporting distributed cognition and hence suggests some new ways of promoting and supporting collaborative learning. The second PI, a learning scientist and mathematics education researcher, brings expertise in math learning and a nuanced understanding of the ways distributed cognition can be leveraged to promote collaborative math learning. It is possible that there are aspects of collaborative learning that are uniquely afforded by the robotics materials of the first PI and the kinds of project-solving challenges that can be built up around them. And there may be new kinds of collaborative behaviors that arise from use of such manipulatives that suggests new avenues for promoting learning. This EAGER project supports first steps in creating synergy between these two approaches and in making these intriguing ideas about promoting collaboration and math learning concrete. The technological innovation in this project is in learning how to use manipulatives with affordances for supporting distributed cognition to promote collaboration and how to effectively integrate use of such manipulates with use of software designed for collaborative math problem solving. The research is directed at shedding light on how to take advantage of manipulatives that can support distributed cognition and hence collaborative learning, and discovering some of the new kinds of collaborative behaviors that might arise from activities with such manipulatives and how to take advantage of those (or alleviate them) in promoting learning.The educational goals being addressed are both broader participation goals and learning goals, the idea being that "play" with engaging robots in the context of learning algebra and other disciplines will draw students in to the subject area at the same time it better promotes their learning. Algebra, in particular, is a gateway to more advanced STEM, and drawing more of the population into STEM careers requires drawing more of them into algebra learning and helping more of the population learn algebra well. The potential broader impacts are particularly strong with respect to gender and diversity. This project represents work in its early states on an untested but potentially transformative idea and is likely to catalyze rapid and innovative advances in the use of modular robotics and other computational manipulatives to broaden participation in STEM disciplines and promote deeper learning in those same disciplines.